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On 26 April 1986, reactor 4 at the Chernobyl power plant underwent a catastrophic failure leading to core explosions and open-air fires. On 11 March 2011, a combination of earthquake and tsunami led to a similar disaster at the Fukushima Daiichi power plant. In both cases, radioactive isotopes were released and contaminated the air, soil and water in a substantial area around the power plants. Humans were evacuated from the immediate regions but the wildlife stayed and continued to be affected by the ongoing high radiation exposure initially and later decayed amounts of fallout dusts with time. In this review, we will examine the significant effects of the increased radiation on vegetation, insects, fish, birds and mammals. The initial intense radiation in these areas has gradually begun to decrease but still remains high. Adaptation to radiation is evident and the ecosystems have dynamically changed from the periods immediately after the accidents to the present day. Understanding the molecular mechanisms that allow the adaptation and recovery of wildlife to chronic radiation challenges would aid in future attempts at ecosystem remediation in the wake of such incidents. [ABSTRACT FROM AUTHOR]

The objective of this paper is to present the results of discussions at a workshop held as part of the International Congress of Radiation Research (Environmental Health stream) in Manchester UK, 2019. The main objective of the workshop was to provide a platform for radioecologists to engage with radiobiologists to address major questions around developing an Ecosystem approach in radioecology and radiation protection of the environment. The aim was to establish a critical framework to guide research that would permit integration of a pan-ecosystem approach into radiation protection guidelines and regulation for the environment. The conclusions were that the interaction between radioecologists and radiobiologists is useful in particular in addressing field versus laboratory issues where there are issues and challenges in designing good field experiments and a need to cross validate field data against laboratory data and vice versa. Other main conclusions were that there is a need to appreciate wider issues in ecology to design good approaches for an ecosystems approach in radioecology and that with the capture of 'Big Data', novel tools such as machine learning can now be applied to help with the complex issues involved in developing an ecosystem approach. [ABSTRACT FROM AUTHOR]